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Electrical impedance tomography (EIT) is a relatively new medical imaging method, which is based on the physiological property that different tissues have different impedances. EIT imaging of brain provides neuroimages by detecting functional impedance changes in the brain caused by cell swelling, blood volume and flow increase, and neuronal depolarisation. These changes are very subtle, therefore imaging analysis is usually needed to enhance the images. In this paper, statistical processing is adopted to analyse brain EIT images. The feasibility of using SPM (Statistical Parametric Mapping), a popular statistical software package used for neuroimages obtained by SPECT/PET or fMRI, to analyse simulated brain EIT images is studied. A scheme of utilizing SPM to interpret brain EIT data is presented. The experimental results suggest that it is reasonable to process brain EIT images with SPM.